Illicit drug marketing on social media in Thailand: a mixed-methods netnography and implications for drug policy

Background Digital technologies have transformed illicit drug markets, with social media increasingly used for distribution and promotion. Our study aimed to characterize illicit drug marketing practices across multiple social media platforms in Thailand using a mixed-methods netnographic approach and to examine their implications for digital surveillance, prevention, and drug policy. Methods We conducted a mixed-methods netnographic study combining quantitative descriptive content analysis with qualitative coding of publicly accessible posts collected across multiple social media platforms in Thailand between January and December 2025. Posts were identified through targeted keyword searches and algorithmically recommended content, followed by manual screening. A curated Thai-language lexicon incorporating drug names, slang terms, euphemisms, coded expressions, and emoji-based representations was used to identify relevant content. Data were processed using Python-based tools, and marketing characteristics were coded across four domains: operational, psychological, conversion, and obfuscation. Descriptive analyses were conducted to summarize patterns across platforms, substance categories, communication features, and posting times. Results A total of 6,446 posts were analyzed. X accounted for 84.7% of posts. Stimulants were the most frequently identified substances (70.7%), followed by new psychoactive substances (22.2%). Indicators of convenience and accessibility were present in 68.7% of posts, while urgency and scarcity cues were observed in 25.9%. Cross-platform transition cues were identified in 41.8% of posts. Coded communication was widespread, including slang substitutions (74.2%) and emoji-based representations (28.6%). The largest proportion of posts (28.3%) by time period was observed during evening hours. Conclusion Illicit drug marketing on social media in Thailand occurs within a multi-platform environment characterized by accessibility-related marketing, coded communication, and cross-platform transition cues. By characterizing these features within the same multi-platform dataset, our study contributes evidence on social media drug markets within the Thai context. These findings support consideration of interaction across platforms in public health surveillance, drug abuse prevention, and drug policy responses.